In many applications such as medical imaging applications, a set of images are used to reconstruct a single focused image and 3D depth profile for visualization. However, the reconstructed image may suffer degradation due to existence of blur and parallax in the original set of images. Blur reduces the sharpness and contrast of the image and occurs when an object is not in complete focus while capturing an image. Parallax causes an apparent displacement in a position of the object while viewed in different images.
These types of defects can be common in images generated by medical diagnosis equipment such as endoscopy, laparoscopy etc. In general, images captured with a moving camera tend to have errors associated with blur and parallax. Specifically, in medical imaging modalities, such inaccurate or degraded images may result in wrong diagnosis.
Object side telecentric lenses are often used to reduce the effects of blur and parallax. However, the size of telecentric lenses may often be comparable to the size of the object itself. Therefore, using such lenses in imaging systems may increase the overall size of the system as well as it associated cost.
In most medical imaging techniques, the reconstructed image is a two dimensional representation of a target such as organs, tumors, bones, and the like. However, these imaging techniques, are not adapted to recover a three dimensional structure of the object. The three dimensional structure of the object or a depth profile may be derived using algorithms based on the shape-from-focus (SFF) principle.
The shape from focus algorithms operates under an assumption that the images do not contain errors due to parallax. Therefore, in images with a substantial amount of parallax, the depth profile of the object estimated using these algorithms may be incorrect.